Print the raw value of a column alone, in pandas?

Question

I have a dataframe:

df = pd.DataFrame([ { \'name\': \'george\', \'age\': 23 }, {\'name\': \'anna\', \'age\': 26}])

Now I want to retrive Ge

Answer 1

Might as well make my comment an answer:

df[df.name == 'george'].age.values[0]

or

int(df[df.name == 'george'].age)

should work

Answer 2

You can use loc + values for converting Serie to numpy array and then select first value by [0]:

print (df.loc[df.name == 'george', 'age'].values)
[23]
print (df.loc[df.name == 'george', 'age'].values[0])
23

Or simply select first value of Series with iloc:

print (df.loc[df.name == 'george', 'age'].iloc[0])
23

Or select first item by iat:

print (df.loc[df.name == 'george', 'age'].iat[0])
23

Or use Series.item:

print (df.loc[df.name == 'george', 'age'].item())
23

---

If possible no match value, above solutions failed.

Then is possible use next with iter trick:

print (next(iter(df.loc[df.name == 'george', 'age']),'no match value'))
23

print (next(iter(df.loc[df.name == 'jano z hornej dolnej', 'age']),'no match value'))
no match value

Answer 3

df = [ { 'name': 'george', 'age': 23 }, {'name': 'anna', 'age': 26}]
k = [x['age'] for x in df if x['name'] == 'george']
print k